Artificial intelligence-driven metabolic engineering is applied to the development of active ingredients in Traditional Chinese Medicine by Zhang Guoqi, Wang Juan

“…In this paper, we introduce AI-driven machine learning algorithms in prediction models, and also review recent research progress on AI-assisted metabolic engineering design and production of high-value compounds, focusing on how to use AI methods to achieve directed evolution of strains.…”
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Predictive Analysis of Cardiovascular Disease Risk Factors in Romania using Machine Learning and Medical Statistics by Radu-Anton MOLDOVAN, Sebastian-Aurelian ŞTEFĂNIGĂ

“…We also used inferential methods such as logistic regression, Cox proportional hazards models, and survival analysis for validation and interpretation of results. …”
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Physiological signal analysis and open science using the Julia language and associated software by George Datseris, Jacob S. Zelko, Jacob S. Zelko

“…First, we highlight available software and Julia communities that provide top-of-the-class algorithms for all aspects of physiological signal processing despite the language’s relatively young age. …”
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Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“…The findings illustrate that RFR is achieving better performance than the other two algorithms, as the predicted magnitudes are close to the actual magnitudes. …”
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Impact of a crop insurance mechanism on credit obtained by smallholders: evidence from “Proagro Mais” in Paraná by Carlos Oñate-Paredes, Vitor Augusto Ozaki

“…The methodology incorporates the propensity score matching (PSM) at the endline year, employing three distinct matching algorithms, and PSM at the baseline, coupled with the difference-in-differences method. …”
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Technical analysis of AI-driven solutions for aligning HR policies with employee satisfaction by Камрун Нахар, Омар Фарук, Захир Райхан

“…The paper delves into the technical architecture, algorithms, and implementation challenges of AI-driven HR solutions, providing a roadmap for organizations to adopt these technologies effectively. …”
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Predicting atezolizumab response in metastatic urothelial carcinoma patients using machine learning on integrated tumour gene expression and clinical data by Chayanit Piyawajanusorn, Ghita Ghislat, Pedro J. Ballester

“…Here we employed eight machine learning (ML) algorithms to predict mUC patient response to atezolizumab using tumours’ gene expression profiling and clinical data from two independent cohorts. …”
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Photography at a Standstill by Geoff Cox

“…What is at stake here, as ever, is a kind of ‘seeing’ (if we continue to call it that) that makes clear what is visible, sensible and knowable, and crucially also what is not. We might call this seeing algorithmically, or seeing like a dataset, or perhaps even seeing like an infrastructure, comprised of fake images that render fake history. …”
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Application of artificial intelligence in electrochemical diagnostics for human health by Koushlesh Ranjan, Basanti Barar, Minakshi Prasad, Gaya Prasad

“…The applications of machine learning (ML) algorithms and AI in electrochemical data analysis have significantly enhanced the sensitivity and specificity of diagnostic methods. …”
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High-sensitivity cardiac troponins: circadian rhythms by A. M. Chaulin, D. V. Duplyakov

“…In addition, there was a need to introduce reference levels of hs-cTnI and hs-cTnT (99 percentile), taking into account sex. Recently, there has also been information about circadian (diurnal) variations in hs-cTnT and hs-cTnI levels. …”
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Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources by Akharakit Chaithanakulwat, Teerawut Savangboon, Nuttee Thungsuk, Taweesak Tanaram, Papol Sardyong

“…Evaluation of the effectiveness of the proposed method usesMATLAB/Simulink simulations, the results being compared to those of theprototype mechanism. We also compare the performance of the MPPT algo-rithm and prototype mechanism, which is connected to a single-phase micro-grid. …”
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Using Symmetries to Investigate the Complete Integrability, Solitary Wave Solutions and Solitons of the Gardner Equation by Willy Hereman, Ünal Göktaş

“…The Gardner and Miura transformations, which connect these equations, are also computed using the concept of scaling homogeneity. …”
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A Computational Sketch-Based Approach Towards Optimal Product Design Solutions by Paschalis Charalampous

“…Using computer vision algorithms, sketches are processed to generate digital design components that serve as inputs for Finite Element Analysis (FEA). …”
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Active location and recovery of unbalance problems in smart distribution networks by LI Yihong, PAN Yicheng, MA Meng, WANG Ping

“…This problem not only causes additional losses, but also triggers equipment damage and power supply interruptions, posing significant threats to the secure and stable operation of smart distribution networks. …”
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Bayesian implementation of Rogers–Castro model migration schedules: An alternative technique for parameter estimation by Jessie Yeung, Monica Alexander, Tim Riffe

“…METHODS: We apply a Bayesian framework for fitting the Rogers–Castro model. We also provide the R package rcbayes with functions to easily apply our proposed methodology. …”
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Pavement condition detection using acceleration data collected by smartphones based on 1D convolutional neural network by Yudong Han, Zhaobo Li, Jiaqi Li

“…Compared with SVM and RBF neural networks, CNN not only saves considerable time by eliminating manual feature extraction operations but also provides higher classification accuracy.…”
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In silico metabolism and toxicity prediction using a knowledge-based approach by Emilio Mateev, Maya Georgieva, Alexandrina Mateeva, Alexander Zlatkov

“…In this study, knowledge-based algorithms were utilized to predict the metabolism and toxicity of a previously identified dual-acting pyrrole-based compound using in silico methods. …”
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Interval price prediction of livestock product based on fuzzy mathematics and improved LSTM. by Weimin Ma, Lingling Peng, Hu Chen, Haisheng Yan

“…An empirical study was conducted on the weekly price data of pork, beef, and mutton in China from 2009 to 2023, incorporating discussions on different embedding dimensions, prediction step, fuzzy granulation window sizes, decomposition techniques, and prediction algorithms. The results indicate that the proposed interval prediction model can not only achieve high accuracy in point prediction, but also better capture price change intervals.…”
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EmRep: Energy management relying on state‐of‐charge extrema prediction by Lars Hanschke, Christian Renner

“…EmRep is tailored to platforms with small energy storage, in which it is found that it doubles effective utility, and also increases performance by 10% with large‐sized storage.…”
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Visual Planarization in Oil Painting Techniques in Digital Information Age by Yiping Zhang

“…The arrival of the digital information age has realized the transformation of people’s production and lifestyle, which has also promoted the vigorous development of the art field. …”
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